This has quietly been a miracle month in medicine.
In the last 5 weeks we’ve got news on:
- retatrutide, the triple agonist GLP-1 from Lilly, basically melting fat and body-wide inflammation at record levels
- RevMed’s new pancreatic cancer drug showing unprecedented abilities to extend life
- small trial of a one-and-done PCSK9 gene editing therapy for slashing LDL cholesterol
- Mayo’s AI-assisted radiology showing vastly improved cancer detection
- this new therapy for metastatic solid tumors
This stuff is at varying levels of evidence. Retatrutide is ~100% on its way, other stuff needs more clinical trial data. But put it together and we’re maybe on the verge of majorly reducing the mortality of heart disease and cancer, the two leading causes of death in America.
If you're an AI fast-follower, it may be time to learn from organizations that moved beyond the AI pilot. While it's unlikely you have an almost $20B 2026 technology budget like JP Morgan, you can learn from their experimentation with AI. https://t.co/7QLwNWo7W9
@emollick NotebookLM + visualization (Nano Banana Pro) + Deep Research is a killer combination that gives you good results while keeping you in control. I’m surprised that other AI labs have not created similar tools.
@MargRev@tylercowen is one of the best at discovering the latest insightful research like this. With so much content being created, I appreciated Tyler's curation and sharing.
Does AI have a "doing" problem?
https://t.co/3fzzeE98UC
What can we infer from (1) Human Intelligence proxies, (2) studies on AI doing, and (3) the doing challenges AI researchers are working to address?
An AI pioneer, Yann Lecun, says his field has been led astray by Large Language Models (since they are not based on factual models of the world, but only on massive correlations and abstractions from them). As a cognitive scientist, I'm sympathetic. https://t.co/vFM0kHO9Tb via @WSJ
@AndrewYNg Well stated. Hopefully we see progress from the many trying to address the challenges of generalization, continuous learning and some kind of world model representation that enables causal and analogy inferences.
@JeffDean Nice insight on the many years of innovation and rigor of Waymo. What have you learned that is critical to building autonomous AI agents that operate in physical and digital worlds?
Nice article @sabrinaa_ortiz AI agents haven't taken all of our jobs just yet. It appears it will take time to train AI agents on the enterprise workflow powered by legacy systems and processes or to redesign the workflow.
https://t.co/YnqgWVTyIk
Nano banana Pro: “i need a flowchart for how to toast bread, make it as wacky and over the top and complicated as possible.“
Not absolutely perfect, but I can’t believe how much there is a coherent through-line, how clear the text is, and also parts of it are actually funny?
@karpathy Great post. Intelligence is achieving goals. Animal achievement of homeostasis and survival through inference and action is impressive. Technology has a long way to go to match it.
The decline of violence continues: Newly released data from the World Bank shows that the global homicide rate has fallen by around a quarter in this century. (Thanks to Fix the News for the item & graph.) https://t.co/PYCMx86bTc
“Creativity is intelligence having fun.” Unleash your creativity and imagination with Marble - our 3D world generation model, now available to everyone!